Parametric model order reduction for a wildland fire model via the shifted POD based deep learning method

This repo contains the source code for a novel non-intrusive model reduction method named sPOD-NN. The script (.ipynb) files for all the test cases are present in the tests folder.

• synthetic.ipynb describes the application of the proposed methods on a 1D synthetically generated data set.
• wildfire1D.ipynb performs the non-inrusive model reduction on a 1D wildland fire model.
• wildfire2D.ipynb shows the application of the proposed methods on a 2D wildland fire model without any external wind.
• wildfire2DNonLinear.ipynb is similar to the previous case but under the influence of a constant unidirectional wind.

The reader is encouraged to try out the sample test case : synthetic.ipynb for which the data generation is already included in the code. However, for other examples the reader can open an issue and the data could be provided thereafter upon request.